Image-to-Image
Diffusers
English
text-generation-inference
template:diffusion-lora
lora
text-image
inference:false
Instructions to use prithivMLmods/Kontext-0811-exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prithivMLmods/Kontext-0811-exp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("prithivMLmods/Kontext-0811-exp") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
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license: other
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license_name: flux-1-dev-non-commercial-license
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license_link: LICENSE.md
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# **Kontext-0811-exp**
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The **Kontext-0811-exp** collection is a suite of fine-tuned adapters for **black-forest-lab’s FLUX.1-Kontext-dev**, developed to extend its visual transformation capabilities across multiple camera perspectives and enhancement modes. Each adapter in this set is trained for a specific spatial or stylistic transformation, ensuring high-quality, context-aware image reinterpretation without loss of realism, lighting accuracy, or environmental consistency.
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## Included Adapters
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inference: false
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license_name: flux-1-dev-non-commercial-license
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license_link: LICENSE.md
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# **Kontext-0811-exp**
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> The **Kontext-0811-exp** collection is a suite of fine-tuned adapters for **black-forest-lab’s FLUX.1-Kontext-dev**, developed to extend its visual transformation capabilities across multiple camera perspectives and enhancement modes. Each adapter in this set is trained for a specific spatial or stylistic transformation, ensuring high-quality, context-aware image reinterpretation without loss of realism, lighting accuracy, or environmental consistency.
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## Included Adapters
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